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Effect of Problem Solving Support and Cognitive Styles on Idea Generation: Implications for Technology-Enhanced Learning

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Effect of Problem Solving Support and Cognitive Styles on Idea Generation: Implications for Technology-Enhanced Learning Journal of Research on Technology in Education, 2007, 40(1), 49–63 Effect of Problem Solving Support and Cognitive Styles on Idea Generation: Implications for Technology-Enhanced Learning Slavi Stoyanov and Paul Kirschner Open University of the Netherlands Abstract This study investigated the effect of two problem-solving techniques: (a) free-association with a direct reference to the problem, called shortly direct, and (b) free-association with a remote and postponed reference to the problem, called remote, on fluency and originality of ideas in solving ill-structured problems. The research design controlled for possible effects of cognitive style for problem-solving—adaptor versus innovator. The results showed that both groups significantly outscored a control group on fluency and originality. The remote group outperformed the direct and control groups on originality, but not on fluency. Innovators scored significantly better than adaptors in the control group on fluency, but not on originality. No significant difference was found between innovators and adaptors in both direct and remote groups. There was no statistical indication for an interaction effect between treatment and cognitive style. Based upon the results of this study, four implications for learning and instruction have been formulated for designing and developing technological arrangements for learning to solve ill-structured problems. These guidelines will support designers in developing instructional design solutions in educational technology applications. (Keywords: learning to solve problems, problem solving support, paradox of knowledge structure, cognitive styles, conceptual design.) Contemporary software design methodology and practice stress that prob- lems in technological design are principally due to problems in the original conceptual design (Constantine, 2001; Holtzblatt, Wendell, & Wood, 2005; Kuniavsky, 2003). If something goes wrong in the conceptual design its nega- tive effects on the next phases of the software development are multiplied. In business applications, this can result in lost capital. If it happens in educational applications, learners will lose interest and leave. The effectiveness of techno- logical solutions that support learning depends heavily on the instructional de- sign strategy implemented in the educational software applications used (Clark, 1994; Russell, 2001; Stoyanov & Kommers, 2006). This article reports on research exploring the impact of different types of problem solving support and their interaction with learner cognitive style on idea generation in ill-structured problem situations. It is intended to generate basic instructional design guidelines for technology-enhanced learning. Solving problems is considered an important competence of students in higher education (Ge & Land, 2004; Jonassen, 2004; Merrill, 2002; Van Mer- riënboer & Kirschner, 2007). It is a crucial task of higher education to help students to develop the knowledge, skills, and attitudes needed to deal with the challenges arising from rapid societal and technological changes. Instructional design, in recognition of this situation, is shifting from emphasis on well-struc- Journal of Research on Technology in Education Copyright © 2007, ISTE (International Society for Technology in Education), 800.336.5191 (U.S. & Canada) or 541.302.3777 (Int’l), [email protected], www.iste.org. All rights reserved. tured learning tasks to ill-structured, real-world, authentic problems. According to Merrill (2002), involving learners in solving real-world problems is the first principle of instructional design. The issue, however, is not only to engage higher education students in solv- ing ill-structured problems but also to provide them with relevant support for learning how to solve ill-structured problems. Instructional design should determine the most effective and efficient conditions of providing both -pro cess and operational support to solving ill-structured problems. Most of the research on problem solving has been focused on process-support identifying the phases of problem solving process, the sequence of which a problem solver should follow (see Jonassen, 2004, for an overview). Less attention has been paid to operational and instrumental problem solving support, in terms of spe- cific techniques and tools that facilitate problem-solving activities within these phases (Ge & Land, 2004; Stoyanov & Kommers, 2006). The knowledge that one should analyze the problem situation, generate ideas, select the most appro- priate, and then implement and evaluate is necessary, but not sufficient. Skills of similar importance are needed for how to proceed in these problem-solving phases, such as what to do when analyzing the problem situation, how to gener- ate ideas, how to select a solution and implement it in practice. The selection and application of these procedures, techniques, and tools depends to a large extent on the desired outcomes of problem-solving determined by the nature of ill-structured problems and the cognitive structures and processes involved in solving them. The first issue to address, therefore, is what the characteristics of ill-structured problems are and what cognitive mechanisms are activated in such problem situations. Characteristics of Ill-Structured Problems Ill-structured problems are characterized by incomplete data or insufficient access to information, existence of alternative and often conflicting approaches, lack of clear-cut problem-solving procedure and no agreement upon what can be accepted as an appropriate solution (Jonassen, 2004; Schön, 1996; Wagner, 1992). Some researchers have challenged the position that ill-structured prob- lems can, in principle, be represented as a set of well-defined problems (Cho & Jonassen, 2002; Hong, Jonassen, & McGee, 2003; Jonassen, 2004; Pretz, Naples, & Sternberg, 2003). These authors argue that different intellectual skills are needed for solving well-defined and ill-structured problems. In our view, ill-structured problems activate specific cognitive processes which may either enable or restrict problem solving. Cognitive Conditions of Ill-Structured Problem Solving Most of the research on problem solving has referred to the limited capac- ity of short-term memory as the most important cognitive factor to deal with (Hambrick & Engle, 2003; Kirschner, 2002; Paas, Renkl, & Sweller, 2004). However, some classical and contemporary cognitive theories have emphasized the crucial role of long-term memory as well (Davidson, 2003; De Bono, 1990; Ericsson & Kintsch, 1995; Gick & Holyoak, 1983; Lubart & Mouchiroud, 0 Fall 007: Volume 40 Number 1 Copyright © 2007, ISTE (International Society for Technology in Education), 800.336.5191 (U.S. & Canada) or 541.302.3777 (Int’l), [email protected], www.iste.org. All rights reserved. 2003; Wenke & Frensch, 2003). Long-term memory may be unlimited in terms of storing information, but in a situation of ill-structured problem solv- ing it is the retrieval of relevant information that is critical. Most of the issues with long-term memory in ill-structured problem situations can be explained by a phenomenon we called it the paradox of knowledge structure.1 This paradox states that the structure of knowledge both enables and restricts ill-structured problem solving. Knowledge organizes itself into knowledge structures (pat- terns, schemas), which are necessary for successful problem solving. These struc- tures are easily recognizable, repeatable and give rise to expectancy. Knowledge structures provide a platform for interpreting incoming information and com- municating new solutions. It is natural for an individual in a problem situation to bring his or her own experience to bear. Knowledge structures are familiar scaffolds that individuals tend to apply in problem situations. Often knowledge structures provide useful short cuts to the solutions. Knowledge structures, however, have some characteristics that may hinder problem solving. A knowledge structure can establish a dominance, which forc- es the problem solver to see and follow only one path and not be aware of other possibilities (Anderson, 1983; De Bono, 1990; Qullian, 1988). Other spread- ing activation paths can be completely ignored, no matter how closely they are positioned to the dominant one. Once a knowledge structure presents itself, the tendency is for it to get larger and more firmly established. This makes it very difficult to break off and jump into an alternative line of reasoning. A well- established knowledge structure may inadequately represent a novel problem situation, thus reducing the problem situation to one that fits that knowledge structure. It is no longer the richness of situation that matters, but the presence or absence of a well-established structure (De Bono, 1990). Management of the restricting part of the paradox of knowledge structure requires a specific type of problem solving support that can cope with the negative effects of knowledge structure. Problem Solving Support in Ill-Structured Situations Research on the role of the external instructional stimuli (e.g., cues, clues, hints, or prompts) in dealing with the negative effects of the paradox of knowl- edge structure returned inconsistent conclusions. Some authors have noticed the positive role of external cues on memory searching in problem-solving situ- ations (Bower & Mann, 1992; Gick & Holyoak, 1983; Halpern, Hanson & Riefer, 1990; Jones, 1982; Paivio, 1986; Runco & Sakamoto, 2003), while oth- ers scholars have
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